Organizations often have to sort through large amounts of data to ensure compliance with governmental regulations, internal controls or policies, risk strategies, or other security and compliance concerns. As a result, various systems exist to address correlation of data by applying logic or rules to analyze the data. However, existing correlation solutions tend to focus on ensuring compliance with specific controls, regulations, or other policies for which the correlation solutions were particularly tailored. Thus, in many cases, a given organization may have to deploy various different correlation engines to ensure compliance across distinct areas or organizational boundaries (e.g., separate correlation engines may be used to ensure compliance with policies for intrusion detection, data integrity, network security, regulatory compliance, internal policies, or other governance, security, and compliance policies).
Although many organizations require data correlation for various needs, existing systems tend to take a divide-and-conquer approach to correlation. Existing correlation solutions tend to only perform specific and isolated types of correlation, for example, thus falling short in providing a comprehensive and future-proof correlation solution. In particular, governmental regulations, internal risk management strategies, or security threats, among other things, may often change on an ongoing and dynamic basis, which may not be addressed adequately using correlation solutions that operate in isolation. With security and compliance only being as strong as a chain's weakest link, existing correlation solutions that perform singular types of correlation cannot provide an integrated, centralized, future-proof solution for real-time monitoring and remediation of security, governance, risk, and compliance.
Accordingly, existing correlation solutions do not provide a mechanism for a plurality of correlation engines to perform various types of correlation on a stream of data. As a result, even when an organization employs best-in-breed correlation solutions for various correlation needs, the lack of interoperability or intercommunication may prevent the various correlation solutions from ensuring system-wide compliance. Furthermore, when multiple correlation solutions operate in isolation of one another, they may be prevented from cooperating with one another to refine precision, instead relying solely on internal logic for functionality.
Existing systems suffer from these and other problems.